Workshop

PLEASE NOTE WORKSHOPS WILL TAKE PLACE AT NYC EVENT SPACE, 4 West 43rd Street, New York NY 10036

Sunday, October 29, 2017 in New York
Full-day: 12:00 - 7:30pm

R for Machine Learning: A Hands-On Introduction

Intended Audience:
Practitioners who wish to learn how to execute on predictive analytics by way of the R language; anyone who wants "to turn ideas into software, quickly and faithfully."

Knowledge Level: Either hands-on experience with predictive modeling (without R) or both hands-on familiarity with any programming language (other than R) and basic conceptual knowledge about predictive modeling is sufficient background and preparation to participate in this workshop.

The 2 1/2 hour "R Bootcamp" is recommended preparation for this workshop.

Workshop Description

This one-day session provides a hands-on introduction to R, the well-known open-source platform for data analysis. Real examples are employed in order to methodically expose attendees to best practices driving R and its rich set of predictive modeling (machine learning) packages, providing hands-on experience and know-how. R is compared to other data analysis platforms, and common pitfalls in using R are addressed.

The instructor, a leading R developer and the creator of CARET, a core R package that streamlines the process for creating predictive models, will
guide attendees on hands-on execution with R, covering:

A working knowledge of the R system

The strengths and limitations of the R language

Preparing data with R, including splitting, resampling and variable creation

Developing predictive models with R, including the use of these machine learning methods: decision trees, support vector machines and ensemble methods

Hardware: Bring Your Own Laptop
Each workshop participant is required to bring their own laptop running Windows or OS X. The software used during this training program, R, is free and readily available for download.

Attendees receive an electronic copy of the course materials and related R code at the conclusion of the workshop.

Instructor

Max Kuhn, Software Engineer, RStudio

Max Kuhn is a software engineer at RStudio, a leading company for R software and tools. He is currently working on improving R's modeling capabilities. He has a Ph.D. in Biostatistics.

Max was a Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years.

Max is the author of eight R packages for techniques in machine learning and reproducible research and is an Associate Editor for the Journal of Statistical Software. He, and Kjell Johnson, wrote the book Applied Predictive Modeling, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015.

He has taught courses on modeling, including many classes for Predictive Analytics World, the useR! conference, the Open Data Science Conference, the India Ministry of Information Technology, and others.